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What is dbt?

The practices of version control, quality assurance, documentation, and modularity facilitate collaboration among data teams in a manner akin to that of software engineering groups. It is essential to treat analytics inaccuracies with the same degree of urgency as one would for defects in a functioning product. Much of the analytic process still relies on manual efforts, highlighting the need for workflows that can be executed with a single command. To enhance collaboration, data teams utilize dbt to encapsulate essential business logic, making it accessible throughout the organization for diverse applications such as reporting, machine learning, and operational activities. The implementation of continuous integration and continuous deployment (CI/CD) guarantees that changes to data models transition seamlessly through the development, staging, and production environments. Furthermore, dbt Cloud ensures reliability by providing consistent uptime and customizable service level agreements (SLAs) tailored to specific organizational requirements. This thorough methodology not only promotes reliability and efficiency but also cultivates a proactive culture within data operations that continuously seeks improvement.

What is Kestra?

Kestra serves as a free, open-source event-driven orchestrator that enhances data operations and fosters better collaboration among engineers and users alike. By introducing Infrastructure as Code to data pipelines, Kestra empowers users to construct dependable workflows with assurance. With its user-friendly declarative YAML interface, individuals interested in analytics can easily engage in the development of data pipelines. Additionally, the user interface seamlessly updates the YAML definitions in real-time as modifications are made to workflows through the UI or API interactions. This means that the orchestration logic can be articulated in a declarative manner in code, allowing for flexibility even when certain components of the workflow undergo changes. Ultimately, Kestra not only simplifies data operations but also democratizes the process of pipeline creation, making it accessible to a wider audience.

Media

Media

Integrations Supported

Databricks Data Intelligence Platform
Snowflake
Airbyte
Azure Marketplace
Cargo
DQOps
Google Cloud BigQuery
Metaphor
Metaplane
OpenText Analytics Database (Vertica)
Paradime
Python
Select Star
Singer
Stonebranch
Union Cloud
Weaviate
Zenlytic
definity
intermix.io

Integrations Supported

Databricks Data Intelligence Platform
Snowflake
Airbyte
Azure Marketplace
Cargo
DQOps
Google Cloud BigQuery
Metaphor
Metaplane
OpenText Analytics Database (Vertica)
Paradime
Python
Select Star
Singer
Stonebranch
Union Cloud
Weaviate
Zenlytic
definity
intermix.io

API Availability

Has API

API Availability

Has API

Pricing Information

$50 per user per month
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

dbt Labs

Date Founded

2016

Company Location

United States

Company Website

www.getdbt.com

Company Facts

Organization Name

Kestra

Date Founded

2022

Company Location

France

Company Website

kestra.io

Categories and Features

Data Lineage

Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

Categories and Features

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